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The purpose of this study is to develop tree-based binary classification models to predict the likelihood of employee attrition based on firm cultural and management attributes.

A data set of resumes anonymously submitted through Glassdoor’s online portal is used in tandem with public company review information to fit decision tree, random forest and gradient boosted tree models to predict the probability of an employee leaving a firm during a job transition.

Random forest and decision tree methods are found to be the strongest attrition prediction models. In addition, compensation, company culture and senior management performance play a primary role in an employee’s decision to leave a firm.

This study may be used by human resources staff to better understand factors which influence employee attrition. In addition, techniques developed in this study may be applied to company-specific data sets to construct customized attrition models.

This study contains several novel contributions which include exploratory studies such as industry job transition percentages, distributional comparisons between factors strongly contributing to employee attrition between those who left or stayed with the firm and the first comprehensive search over binary classification models to identify which provides the strongest predictive performance of employee attrition.

The purpose of this paper is to identify the attributes that predict customer attrition behavior in the brokerage and investment banking sectors.

The authors analyze the complete stock trading records and customer profiles of 458,098 retail customers from a Korean brokerage house. The authors develop customer attrition prediction models and further explore the practicality of these models using statistical classification techniques.

The results from three different binary selection models indicate that customer transaction patterns effectively explain the attrition of active retail customers in subsequent periods. The study results demonstrate that monetary value variables are the most critical for predicting customer attrition in the securities industry.

This study contributes to the customer attrition literature by documenting the first large-scale field-based evidence that confirms the practicality of the canonical recency, frequency and monetary (RFM) framework in the investment banking and brokerage industry. The findings advance previous survey-based studies in the financial services industry by identifying the attributes that predict customer attrition behaviors in the securities industry.

The outcomes can be easily operationalized for attrition prediction by practitioners in financial service firms. Moreover, the ex post density of inactive customers in the top 10 percent most-likely-to-churn group is estimated to be five to six times the ex ante unconditional attrition ratio, which ascertains that the attributes recognized in this study work well for the purpose of target marketing.

While the securities industry is regarded as one of the most information-intensive industries, detailed empirical investigation into customer attrition in the field has lagged behind partly due to the lack of suitable securities transaction data and demographic information at the customer level. The current research fills this gap in the literature by taking advantage of a large-scale field data set and offers a starting point for more elaborate studies on the drivers of customer attrition in the financial services sector.

Given a growing literature indicating that downsizing is not an effective way to address financial decline, having either little impact or negative impact on the financial health or market valuation of financially troubled companies, what is the alternative for those companies in financial trouble? Three sets of alternatives to downsizing are available to companies suffering financial trouble: strategies addressing personnel/fix costs, strategies focused on addressing cost cutting/variable costs and strategies addressing strategic planning/revenue. Although alternatives to downsizing have been identified, little research has been conducted comparing the impact of downsizing vs alternatives to downsizing on firm performance. The paper aims to discuss this issue.

This present study looked solely at strategies focused on addressing personnel/fix costs. Focusing primarily on forced attrition (downsizing) vs temporary attrition and/or natural attrition, this research attempts to determine whether specific groupings of alternatives to downsizing are more effective at addressing financial decline that companies find themselves in as compared to downsizing. This included relying on temporary attrition, natural attrition or doing nothing at all.

The research presented here indicates that various alternatives to downsizing have an immediate positive impact on measures of profitability and a positive long-term impact on one measure of efficiency: revenue per employee. Evidence shows that temporary attrition leads to better financial outcomes than natural attrition than forced attrition or downsizing.

The research presented here indicates that various alternatives to downsizing have an immediate positive impact on measures of profitability and a positive long-term impact on one measure of efficiency: revenue per employee. This has implications for managers put in the position of having to make a decision whether to downsize or not.

Research that follows people over a period of time (longitudinal or panel studies) is increasingly recognised as of great importance in helping us to understand the ageing process and changes over time in the lives of older people. If people drop out of studies ‐ which older people are more likely to do ‐ the value of the study diminishes. This research draws on evidence from ongoing and previous longitudinal studies of people aged 55 and over to examine what factors encourage the retention of participants and what causes them to drop out. The research is synthesising existing evidence, drawing together the experiences of researchers involved in longitudinal studies, and collecting some new evidence about the views of survey participants. This article reports on the first part of the research by drawing together evidence from other studies. These show that there are some factors that are related to attrition whereas for others the evidence is mixed. Methods employed by these studies to reduce attrition and retain participants are examined. It must be noted that apart from the consistent finding that attrition is associated with age, education, socio‐economic status and cognitive impairment, not all studies examined the same variables; some only being explored by one study. This makes it difficult to draw any further conclusions and indicates that attrition needs to be addressed in a uniform manner by more studies. This article identifies some implications for policy‐makers and practitioners.

Do female police recruits drop out of police education and/or leave the profession more often than men, and has this changed over time? Can gender differences be explained by the background characteristics and family obligations of the recruits?

This paper employs administrative registry data covering all individuals admitted to the police academy (1995–2010, N = 6570) and all academy recruits employed in the Norwegian police (1992–2014, N = 7301). The paper analyses the data using discrete-time logistic regression and coarsened exact matching.

The levels of dropout and attrition are generally low. However, female recruits have a somewhat greater tendency both to drop out of education and to leave the force. The gender differences are quite stable, although the percentage of female recruits has risen sharply. Family obligations do not seem to explain female attrition from the police force.

Because women tend to leave the police more often than men, further research is suggested in investigating female police recruits’ experiences. However, the relatively low level of dropout and limited gender differences also provide a reason to question whether stories of the police as a male-dominated profession not adapted to women are valid across time and in different settings.

This study provides exhaustive and detailed longitudinal data not previously available in studies of police careers. This study also tracks attrition in a period that has involved both increased numerical representation of women and changes in police culture, while accounting for other observable differences between male and female police officers. Contrary to common explanations, there is limited importance of family obligations and altered gender composition.

The purpose of this paper is to determine whether teachers with high value‐added scores (as a measure of teacher quality) stay or left test grades and subjects in a medium‐sized school district.

Panel data for this paper encompass teachers providing math and reading instruction and link to individual students in grades 3‐10 from a single Florida school district (2000‐2001 to 2004‐2005). Value‐added modeling is used to estimate a measure of teacher quality, which is entered into binomial logistic regression models.

This paper finds a negative relationship between reading teachers' value‐added scores and attrition (p<0.05) – a finding consistent with the few that have examined the relationship between value added and teacher attrition. A significant relationship is not found between math value added and attrition. There is also no significant relationship between value added and transferring. Secondary and alternatively certified teachers are more likely to exit tested grades/subjects. Classroom percentages of students enrolled in the free/reduced lunch program (a proxy for poverty) are associated with leaving among math and reading teachers.

Not all turnover is negative. Evidence from this paper suggests that schools are not losing the best teachers from tested subjects and grades – those in which schools and school leaders are held accountable. While there are costs associated with turnover, it can serve as an important matching function between workers and employers.

Only, a few published studies have utilized value‐added scores as the measure of teacher quality and tested their relationship with teacher attrition.

This study explored attrition from a novice health researcher training program. The aim of this paper was to identify factors contributing to attrition from the RRCBP that if understood could decrease attrition from this standalone researcher training program.

Using a capacity building framework, this case-control study compared demographic characteristics and features of 30 withdrawn research trainees to 68 graduated trainees from the Rural Research Capacity Building Program, run by the Health Education and Training Institute of New South Wales, Australia between 2006 and 2010. Data were analysed using Exact Logistic Regression, Chi-square and Fisher's Exact tests.

An attrition rate of 29 per cent was associated with a range of individual, organisational and supra-organisational factors. Withdrawals occurred prior to ethics submission (n=13, 43 per cent), after unsuccessful ethics submission (n=8, 27 per cent), or after receiving ethics approval (n=9, 30 per cent). Clinicians were less likely to withdraw than non-clinical staff (p=0.03). Profession, project ownership, funding sources and type of research were not significant factors in attrition, while the effect of location was mixed indicating a potential impact of peer support networks in areas with high numbers of trainees.

This research demonstrates attrition from a research training program is associated with trainees receiving appropriate and timely support. In the formative stages researchers require support, particularly those working in professional or geographical isolation.

This study is the first of its kind in examining in detail reasons for withdrawal from a standalone research training program and will allow coordinators of similar programs to target support to vulnerable research trainees at critical time points.

Managing attrition is a major challenge for outsourcing vendors. Literature on management control in offshore outsourcing is dominated by the formal approaches to control design, which do not adequately consider the influence of contextual factors. This article aims to adopt the lens of institutional theory, and use empirical data gathered from case studies in both the UK and India to improve the understanding of the institutional logics that shape the control of attrition.

This article draws on in‐depth qualitative research undertaken with directors and senior managers in client and vendor firms engaged in outsourcing relationships that span both corporate and national boundaries. Drawing on empirical data from the UK and India, the interplay between the management control of attrition and contextual factors is analysed, and the practices adopted to manage these contextual factors are also identified and discussed.

The analysis presents relevant aspects of the regulative, normative and cognitive institutions inhabited by vendor firms and the challenges such aspects present for managing attrition. The dynamics of institutions and control are discussed in the area of attrition, and the interplay between institutions and control is outlined. The regulative, normative and cognitive institutions inhabited by vendor firms contrast markedly to that of the client in relation to social and legal rules, norms and practices.

The paper develops a theoretical basis for linking control and context in offshore outsourcing, drawing on the work of Scott in institutional theory, and Friedland and Alford, in institutional logics. This paper offers an alternative conceptualisation of control in attrition based upon rationalistic modelling through institutional logics.

This paper offers key implications for research, in improving the understanding of contextual factors and management control in global outsourcing relationships. Both clients and vendors in offshore outsourcing need to be aware of the influence of contextual factors when managing attrition.

The interplay of institutional logics and implications on the control of attrition provides an interesting approach to understanding how firms manage attrition in offshore outsourcing.

This paper aims to focus on the experience of monitoring of first year student attrition in a large metropolitan multi‐campus university during 2004‐2010. The paper seeks to discuss the trends in student attrition which have been found and identify key issues which have been and need to be addressed by the university in order to increase retention.

A specially designed survey was repeated across the years and completed over the period by 2,085 undergraduate students who left the university before the end of their first year of study.

The most important of issues which need to be addressed by the university are sufficient, correct and clear information provided to prospective students about the course before they enrol and high‐quality course advice about subject choices after enrolment.

Sufficient, correct and clear information provided to prospective students about the course remains an area in need of improvement. Therefore, in marketing the university both locally and internationally, a particular focus needs to be on direct contact by knowledgeable staff with prospective students.

Marketing of courses with support of academic staff, course advisers and program heads should give particular focus to the clear management of student expectations. Targeted marketing at the school/course level is needed in order to ensure clear and specific expectations management. This approach, if adopted, should help reduce attrition among those students for whom “the course wasn't what they expected”.

Improving university student retention is one of the high‐priority government targets in developed countries such as Australia, the UK and the USA. At the same time, higher education providers in these countries try to increase the participation of students from traditionally underrepresented groups of population in order to meet the aspirations of governments. The changes in policies and performance‐based funding require universities to align the growth of numbers of students from underrepresented groups with a range of academic and general support services to support student transition, retention and completion. An important aspect for universities is to ensure that low entry standards do not compromise graduate exit standards.

Evaluating attrition trends through systematic feedback from withdrawing students can help universities identify key issues which need to be addressed in order to increase retention. Further, it may help narrow down the list of such issues to one or two most persistent over a number of years. For example, for the university described in this study, the steadiest factor behind student attrition is quantity and quality of information provided to prospective students about the course before they enrol. If this issue is appropriately addressed, and provided all other important attrition factors are closely monitored, the university can significantly increase the likelihood of student retention and success.

Research questions that this paper attempts to answer are – do the features in general email communication have any significance to a teaching faculty member leaving the business school? Do the sentiments expressed in email communication have any significance to a teaching faculty member leaving the business school? Do the stages mentioned in the transtheoretical model have any relevance to the email behaviour of an individual when he or she goes through the decision process leading to the decision to quit? The purpose of this paper is to study email patterns and use predictive analytics to correlate with the real-world situation of leaving the business school.

The email repository (2010–2017) of 126 teaching faculty members who were associated with a business school as full-time faculty members is the data set that was used for the research. Of the 126 teaching faculty members, 42 had left the business school during this time frame. Correlation analysis, word count analysis and sentiment analysis were executed using “R” programming, and sentiment “R” package was used to understand the sentiment and its association in leaving the business school. From the email repository, a rich feature set of data was extracted for correlation analysis to discover the features which had strong correlation with the faculty member leaving the business school. The research also used data-logging tools to extract aggregated statistics for word frequency counts and sentiment features.

Those faculty members who decide to leave are involved more in external communication and less in internal communications. Also, those who decide to leave initiate fewer email conversations and opt to forward emails to colleagues. Correlation analysis shows that negative sentiment goes down, as faculty members leave the organisation and this is in contrary to the existing review of literature. The research also shows that the triggering point or the intention to leave is positively correlated to the downward swing of the emotional valence (positive sentiment). A number of email features have shown change in patterns which are correlated to a faculty member quitting the business school.

Faculty members of only one business school have been considered and this is primary due to cost, privacy and complexities involved in procuring and handling the data. Also, the reasons for exhibiting the sentiments and their root cause have not been studied. Also the designation, roles and responsibilities of faculty members have not been taken into consideration.

Business schools all over India always have a challenge to recruit good faculty members who can take up research activities, teach and also shoulder administrative responsibilities. Retaining faculty members and keeping attrition levels low will help business schools to maintain the standards of excellence that they aspire. This research is immensely useful for business school, which can use email analytics in predicting the intention of the faculty members leaving their business school.

Although past studies have studied attrition, this study uses predictive analytics and maps it to the intention to quit. This study helps business schools to predict the chance of faculty members leaving the business school which is of immense value, as appropriate measures can be taken to retain and restrict attrition.